4.7 Article

Digital mapping and spatial characteristics analyses of heavy metal content in reclaimed soil of industrial and mining abandoned land

期刊

SCIENTIFIC REPORTS
卷 8, 期 -, 页码 -

出版社

NATURE PUBLISHING GROUP
DOI: 10.1038/s41598-018-35624-9

关键词

-

资金

  1. National Key Research and Development Program of China [2016YFD0300801]
  2. National Natural Science Foundation of China [41471186]

向作者/读者索取更多资源

The reclaimed soil properties of industrial and mining wasteland have strong spatial specificity. The paper aimed to screen out a hybrid multifractal and kriging (Named as Mkriging) method for digital mapping and scientifically reveal the spatial distribution characteristics in view of heavy metal in reclaimed soil of industrial and mining abandoned land. The results of the study showed that for reasons of history and reclamation, the original samples of heavy metals in reclaimed soil of industrial and mining abandoned land showed a very large range and variation degree, the C-0/(C-0 + C-1) values of different heavy metals basically were all greater than 50%, random factors played a dominant role. The five kinds of heavy metals in reclaimed soil were in the following descending order in terms of homogeneity: Cd, As, Hg, Ni and Cr. Compared with ordinary Kriging method, the relative improvement of root mean squared errors of elements Cd, Hg, As, Cr and Ni based on Mkriging were 95.28%, 61.74%, 78.54%, 82.51% and 83.58% respectively. The higher the fractal degree of heavy metals in reclaimed soil was, the higher the prediction accuracy will be. Mkriging method is more suitable for spatial prediction of heavy metals in reclaimed soil of industrial and mining abandoned land.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Environmental Sciences

Influencing factors and prediction of arsenic concentration in Pteris vittata: A combination of geodetector and empirical models

Weibin Zeng, Xiaoming Wan, Mei Lei, Gaoquan Gu, Tongbin Chen

Summary: Phytoextraction using hyperaccumulator Pteris vittata has been applied for arsenic removal, but standardization of this technology faces challenges due to differences in studies. Factors influencing arsenic concentration in P. vittata include soil components like organic matter and available arsenic, as well as environmental factors such as total potassium concentration and rainfall. Predictive models established for greenhouse and field conditions showed the importance of soil available arsenic and rainfall in determining arsenic concentration in P. vittata, indicating potential for improving phytoextraction efficiency and technological standardization.

ENVIRONMENTAL POLLUTION (2022)

Article Environmental Sciences

Method on site-specific source apportionment of domestic soil pollution across China through public data mining: A case study on cadmium from non-ferrous industries

Changhe Wei, Mei Lei, Tongbin Chen, Chenghu Zhou, Runyao Gu

Summary: By estimating the cumulative Cd emission of non-ferrous metal enterprises (NMEs) in China and identifying the emission hotspots, this study provides insights into the spatial distribution of Cd pollution. A significant positive correlation was observed between NMEs and soil Cd, except for secondary smelting enterprises. A modified approach for regional source apportionment of soil pollution was proposed to obtain a more realistic and precise drawing. This study highlights the importance of targeted management and control of Cd pollution in key industries and hotspots.

ENVIRONMENTAL POLLUTION (2022)

Article Environmental Sciences

Spatial heterogeneity of human lifespan in relation to living environment and socio-economic polarization: a case study in the Beijing-Tianjin-Hebei region, China

Changhe Wei, Mei Lei, Shaobin Wang

Summary: This study investigates the spatial heterogeneity and influence factors of public lifespan in the Beijing-Tianjin-Hebei (BTH) region of China, by using geographically weighted regression (GWR) to integrate environment and socio-economic factors. The results reveal significant spatial variability in lifespan indicators, with socio-economic factors having a dominant influence on lifespan.

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2022)

Article Engineering, Environmental

Potential, risks, and benefits of the extract recycled from Pteris vittata arsenic-rich biomass as a broiler growth promoter

Wen Cai, Tongbin Chen, Mei Lei, Xiaoming Wan

Summary: Extract from arsenic-rich biomass, such as rutin, can promote broiler growth and reduce antibiotic usage in the industry. However, it may pose health and environmental risks, while also benefiting the sustainability of phytoremediation and broiler industry through waste exchange.

JOURNAL OF HAZARDOUS MATERIALS (2022)

Article Environmental Sciences

The key nodes and main factors influencing accumulation of soil arsenic in Pteris vittata L. under field conditions

Jun Yang, Yunxian Yan, Nanjia Lu, Xiaoming Wan, Junxing Yang, Huading Shi, Tongbin Chen, Mei Lei

Summary: This study identified the inflection points and main influencing factors for arsenic accumulation in Pteris vittata under field conditions, highlighting soil humidity as a key factor affecting arsenic accumulation. The results showed that increasing soil humidity can substantially improve arsenic extraction efficiency in P. vittata, providing valuable insights for remediation of arsenic-contaminated soils under similar climatic conditions.

SCIENCE OF THE TOTAL ENVIRONMENT (2022)

Article Environmental Sciences

Temporal and spatial differentiation characteristics of soil arsenic during the remediation process of Pteris vittata L. and Citrus reticulata Blanco intercropping

Yunxian Yan, Jun Yang, Xiaoming Wan, Huading Shi, Junxing Yang, Chuang Ma, Mei Lei, Tongbin Chen

Summary: This study clarified the spatio-temporal characteristics of arsenic during the Pteris vittata L.-Citrus reticulata Blanco intercropping process through a pot positioning experiment. The results showed a significant decrease in arsenic concentration in Citrus reticulata leaves in the intercropping system, reducing pollution risks.

SCIENCE OF THE TOTAL ENVIRONMENT (2022)

Article Environmental Sciences

Catalytic efficiency of soil enzymes explains temperature sensitivity: Insights from physiological theory

Chaoyang Liu, Haixia Tian, Xiaoyue Gu, Ni Li, Xiaoning Zhao, Mei Lei, Hattan Alharbi, Mallavarapu Megharaj, Wenxiang He, Yakov Kuzyakov

Summary: Soil enzymes play a crucial role in carbon and nutrient cycling and are sensitive to warming. This study examines the enzyme responses to warming based on the Arrhenius law and physiological theory. The results show that enzyme catalytic efficiency remains stable at low temperatures and increases at higher temperatures, highlighting the importance of considering physiological theory in understanding enzyme activities under warming.

SCIENCE OF THE TOTAL ENVIRONMENT (2022)

Article Environmental Sciences

Source-specific health risks apportionment of soil potential toxicity elements combining multiple receptor models with Monte Carlo simulation

Mei Lei, Kai Li, Guanghui Guo, Tienan Ju

Summary: Understanding the sources and risks of soil PTEs is important for pollution control and risk prevention. This study identified and apportioned the sources of soil PTEs in a mining and industrial area in southwestern China using statistical methods and models. It was found that smelting activities related to arsenic were the main source of pollution and posed the highest health risks.

SCIENCE OF THE TOTAL ENVIRONMENT (2022)

Article Environmental Sciences

Digital Mapping of Soil Organic Carbon with Machine Learning in Dryland of Northeast and North Plain China

Xianglin Zhang, Jie Xue, Songchao Chen, Nan Wang, Zhou Shi, Yuanfang Huang, Zhiqing Zhuo

Summary: This study provides the up-to-date spatial distribution map of soil organic carbon in drylands of Northeast and North China Plain using machine learning algorithms. The results showed that SOC increased from south to north and decreased with soil depths. Random Forest performed better in terms of prediction accuracy and robustness. Soil, parent material, and organism were identified as the most important variables in SOC prediction.

REMOTE SENSING (2022)

Article Environmental Sciences

Apportionment and Spatial Pattern Analysis of Soil Heavy Metal Pollution Sources Related to Industries of Concern in a County in Southwestern China

Xiaohui Chen, Mei Lei, Shiwen Zhang, Degang Zhang, Guanghui Guo, Xiaofeng Zhao

Summary: This study used the integration of geostatistical and chemometric methods, including positive matrix factorization (PMF), cokriging (CK), and locally weighted regression (LWR), to identify subregions with different industries and analyze the sources, spatial patterns, and prevention distance of soil heavy metal pollution in a county-level area.

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2022)

Article Computer Science, Information Systems

Grid-Scale Regional Risk Assessment of Potentially Toxic Metals Using Multi-Source Data

Mulin Chen, Hongyan Cai, Li Wang, Mei Lei

Summary: Understanding the risks posed by potentially toxic metals (PTMs) in large regions is crucial for environmental management. However, traditional field sampling or administrative statistical data methods are time-consuming and not precise. This study utilized multi-source data and proposed a novel model based on atmospheric deposition to assess PTMs in Yunnan Province, China at a 1 km scale. The findings demonstrate the reliability and cost-effectiveness of multi-source data for assessing pollution risks in large areas.

ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION (2022)

Article Environmental Studies

System Cognition and Analytic Technology of Cultivated Land Quality from a Data Perspective

Huaizhi Tang, Jiacheng Niu, Zibing Niu, Qi Liu, Yuanfang Huang, Wenju Yun, Chongyang Shen, Zejun Huo

Summary: As the attention to cultivated land quality increases, there are widespread connotation generalization and cognitive bias, which pose many challenges to the investigation, evaluation, and data analysis of regional cultivated land quality. Therefore, a systematic and interdisciplinary cognitive approach to cultivated land quality is urgently needed. In this study, a conceptual framework for cultivated land quality analysis was developed, including ontology, mapping, correlation, and decision models. The framework demonstrated strong adaptability, efficiency, and scalability, offering a theoretical direction for further studies on cultivated land quality evaluation.
Article Environmental Sciences

High-Resolution Mapping of Soil Organic Matter at the Field Scale Using UAV Hyperspectral Images with a Small Calibration Dataset

Yang Yan, Jiajie Yang, Baoguo Li, Chengzhi Qin, Wenjun Ji, Yan Xu, Yuanfang Huang

Summary: This study aims to test the feasibility of using UAV hyperspectral data to map soil organic matter at a 1 m resolution. The results show that the random forest model based on UAV hyperspectral data can successfully predict soil organic matter with high accuracy, compared to other prediction methods.

REMOTE SENSING (2023)

Article Environmental Studies

Can We Prevent Irreversible Decline? A Comprehensive Analysis of Natural Conditions and Quality Factor Thresholds of Cultivated Land in China

Huaizhi Tang, Zibing Niu, Feng Cheng, Jiacheng Niu, Leina Zhang, Mengyu Guo, Yuanfang Huang

Summary: This study focuses on evaluating the natural resource thresholds of cultivated land in China at a regional scale. By developing innovative classification and short-board identification methods and adopting various technical analyses, the study finds that China mainly maintains medium-quality land with certain limiting factors. There are notable differences in the restrictive factors of cultivated land quality among regions. The study also proposes different management strategies based on regional differences in cultivated land quality.
Article Environmental Studies

Determinants of Soil Bacterial Diversity in a Black Soil Region in a Large-Scale Area

Jiacheng Niu, Huaizhi Tang, Qi Liu, Feng Cheng, Leina Zhang, Lingling Sang, Yuanfang Huang, Chongyang Shen, Bingbo Gao, Zibing Niu

Summary: This study investigated the influencing factors of soil bacterial diversity in a black soil region. The results showed that broad effect, accumulated temperature, and pH were the main factors affecting soil bacterial diversity. The broad effect was more significant in the spatial effect, possibly due to local landscape configuration.
暂无数据